Many Implantable Medical Devices (IMDs) measure physiological parameters of a patient's body. These signals may be used for diagnosis, and to enable a physician to render appropriate treatment. Examples of physiologic parameters measured by an IMD may include body temperature and pressure, tissue impedance, and tissue oxygen levels. As another example, it is often desirable to measure a voltage existing between two points in the body. This measurement is typically obtained between two electrodes.
Many types of IMDs obtain voltage measurements for use in the diagnosis and treatment of medical conditions. For example, pacemakers, defibrillators, cardioverters, and hemodynamic monitors often measure electrocardiograms (EGMs), which are voltage signals measured within a patient's cardiovascular system and used in the diagnosis and treatment of heart conditions. These signals may be transferred immediately to external devices for use in diagnosis, or may be temporarily stored in the IMD and transferred for later external use. These signals may also be used by the IMD to adjust treatment.
One problem with obtaining accurate voltage measurements within a patient's body involves baseline wander. Baseline wander involves large amplitude, low-frequency, non-physiological signals that can saturate a measurement system, resulting in the loss of patient signal information. There are several sources of baseline wander that often affects internal devices. Patient movement, for example, may disturb the electrical connection of an electrode, causing a low frequency signal to be superimposed on the physiologic signal. Another source of baseline wander in pacing devices, cardioverters, and defibrillators, involves the delivery of electrical stimulus to tissue in the region of the electrode. This delivery of electrical energy creates an electrical field that interferes with the physiological signal being measured.
FIG. 2 shows how baseline wander can affect the measurement of a physiological signal such as an EGM. In FIG. 2, an initial portion 21 of curve 20 has a relatively large rate of change as will occur upon delivery of electrical stimulus to tissue surrounding an electrode. The bias current signal eventually begins to stabilize, as indicated by a portion 23 of curve 20. The bias current signal results in a significant rate of change of the combined input signal, wherein the combined signals include the baseline wander imposed on the physiological signal being measured. This rate of change of the combined input signal is referred to herein as the slew rate. When the bias current signal eventually starts to stabilize, the slew rate of the combined input signal is reduced.
Conventional techniques can be used to compensate for the "offset" caused by the baseline wander in order to keep the combined input signal from saturating the system. However, conventional compensation techniques are generally inadequate for the high slew rate of the combined signal caused during the initial period of the bias current signal as discussed above. Additionally, when conventional techniques are used to compensate for the offset, the waveform morphology is changed. This change makes patient diagnosis and monitoring more difficult. For example, by using a conventional filter having a cut-off frequency selected to remove the offset resulting from baseline wander, waveform characteristics used to diagnose ischemia are filtered from the measured signal.
FIG. 3 is a block diagram illustrative of conventional digital signal measuring system of the type that may be used to measure a physiological signal. Signal measuring system 10 includes a preamplifier 31, a high pass filter (HPF) 33, an analog-to-digital converter (ADC) 35 and a second HPF 37. As will be appreciated by those skilled in the art, signal measuring system 10 includes an anti-aliasing filter (not shown) configured to filter out frequency components of the input signal above one-half of the sample rate of ADC 35.
In this example, the passband of HPF 33 is set at about 0.03 Hz, while the passband of HPF 37 is set at about 0.02 Hz. This gives a passband with a lower edge of 0.05 Hz. This performance is consistent with industry standards for diagnostic quality surface electrocardiograms. Unfortunately, the baseline wander signal has frequency components above 0.05 Hz. Thus, in this example, HPF 33 passes the baseline wander signal along with the input signal to cause the saturation problem described above.
One conventional solution to this problem is to increase the dynamic range of the system. Current industry standards require a dynamic range of at least 10 mV (i.e. ranging from .+-.5 mV). Diagnostic and interpretive algorithms require resolution of 5.0 .mu.V. This range is adequate for physiological signals that do not include baseline wander. Sources of baseline wander discussed above dictate that the dynamic range would have to be increased to greater than 150 mV. However, to increase the dynamic range and maintain a given resolution would require an increase in the number of bits of the analog-to-digital conversion. For example, a twelve-bit ADC can be used for 20 mV dynamic range and 5 .mu.V resolution. However, a sixteen-bit ADC may be required for 160 mV dynamic range and the same 5 .mu.V resolution. The cost of a sixteen-bit ADC is significantly higher than a twelve-bit ADC, which undesirably increases the cost of the signal measuring system. In addition, a sixteen-bit ADC utilizes more power than a twelve or eight-bit ADC. This is undesirable in the context of an Implantable Medical Device (IMD) wherein power conservation is a primary design consideration.
Another solution to a related problem of measuring an external electrocardiograph (ECG) signal is disclosed in co-pending and commonly assigned U.S. patent application Ser. No. 09/013,570, entitled "Digital Sliding Pole Fast Restore For An Electrocardiograph Display," Stice, et al. Although the disclosed digital sliding pole invention represents a substantial improvement over the prior art, further improvement is, of course, generally desirable. Thus, there is a need for a low-cost, energy-efficient, physiological signal measuring system for use in an IMD having a relatively large dynamic range and high resolution. The system should minimize the changes in the morphology of the physiological signal being measured so that the ability to provide accurate patient diagnoses is not compromised.